Subscribe
Share
Share
Embed
Do Good Work is not a label but a way of living.
It is the constant and diligent effort to achieve a new level of excellence in one’s own life.
It is the hidden inner beauty behind the struggle to achieve excellence.
It is not perfect but imperfect.
It is the effort, discipline and focus that often goes unnoticed.
The goal of this podcast is to highlight that drive.
The guests I have on this show emulate this drive in their own special way. You’ll be able to apply new ideas into your own life by learning from them.
We will also have 1on1 episodes with me where we’ll dive into my own experiences with entrepreneurship and leadership.
Every episode is designed to provide you with ideas that you can apply and grow in excellence in all areas of your life, business and career.
Do Good Work,
Raul
INTRO
PODCAST
raul-_1_05-15-2025_110521: All right.
Welcome back to the pod I
Today I have Cynthia and Rich.
Both are a power couple building.
There's startup.
Let's dive in.
Can you tell us a little bit more
about you and what you're building?
cynthia-abbott-kerr_1_05-15-2025_110521:
Certainly, so I'm Cynthia Abbott Kerr.
I'm the founder of Pay ai.
And we work with businesses to help them
design and align their pay strategy.
I'm an unlikely founder.
And that I spent 15 years in corporate
America climbing the corporate ladder.
And I was actually on a
trip to Japan with Richard.
We were walking to Maing Temple and
he said, I really think you should
try to start your own business.
And I hemmed and hawed and, there were
competitors in the space and all this
and that, and he was like, I'll build
all the tech for you, get out there, get
out there with it, I'll build the tech.
I should also preface it was like a
hundred degrees that day in Tokyo, so I
might have been delirious when I agreed.
I.
Chapter.
But that's how well Pink came about.
That's why when you look at our
original, I actually have a sticker here.
When you look at a lot of our original
logo design, we had, the Lotus Flower,
Is still prominent on our website, but
a lot of that was an homage to our trip
to Japan and how, enlightening that
was, that, that led to this chapter.
So that's
raul-_1_05-15-2025_110521:
that's pretty sweet.
That's pretty cool.
And also the heat.
Yeah.
Playing a role with the
decision making here.
Someone was delirious.
cynthia-abbott-kerr_1_05-15-2025_110521:
I was delirious.
And it's the longest mile I've ever
walked from like the entrance of the
gate to get to the actual temple.
raul-_1_05-15-2025_110521: Oh my gosh.
cynthia-abbott-kerr_1_05-15-2025_110521:
with this person you trust that you've
been with for almost two decades.
And they're like, you can do it.
You should do it.
And you're like, I, the Tiger's
like playing in your mind.
And by the
raul-_1_05-15-2025_110521: Oh my gosh.
cynthia-abbott-kerr_1_05-15-2025_110521:
You're like, I can definitely do it.
I can do that.
Okay.
raul-_1_05-15-2025_110521: I like it.
That is part of the journey.
That is a great metaphor.
And it was your real experience.
But how is it like building, we will have
to dive into what AI means here and how
you're building and leveraging AI for it.
But how is it building.
An AI company nowadays.
And how are you thinking strategically,
not just to implement it in your
workflows, but also the ethics
and the compliance behind it?
'cause you're working in a very
compliant industry when it comes
to law with pay and comp and hr.
So walk us through that.
'cause that that in itself
is its own obstacle really.
cynthia-abbott-kerr_1_05-15-2025_110521:
I, I think, and this is where Rich
can definitely bring his AI expertise.
I think it's the blend of both worlds.
So I'll talk to him from a space of,
here's what I've seen as a practitioner.
Here's the pain points,
here's the strains.
How do we make that?
A less complicated, and he'll say,
okay, based on all that information,
here's what I think we should do.
While keeping in mind all of the
tech constraint and all of the
security that we have to maintain.
When we.
Started pay, we built on the
foundation of being SOX two compliant.
raul-_1_05-15-2025_110521: Yep.
cynthia-abbott-kerr_1_05-15-2025_110521:
So you know, we have healthcare
businesses that we support.
We work with clients that
are in the FinTech space.
So we started from a place of
being able to provide a service
that could be scrutinized
Could stand up to heavy regulation.
We were just on a call and right
now everybody's trying to figure
out artificial intelligence.
And what I call like free range, right?
Like your organic chickens
are just out there,
That's dangerous.
raul-_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
You wanna be thoughtful and
measured in how you are bringing
an AI into your organization.
Especially artificial intelligence is
gonna impact compensation because just
going out and calling out into the
darkness, it's like drinking expired milk.
raul-_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
What's it gonna do for you?
But Rich, that's really, I think,
where your expertise comes in as well.
As far as like, how are we thinking
about the build, the technology
the technology that you've built.
You have two patents.
dr--rich-kerr_1_05-15-2025_110521: Okay,
calm down with the pun, with the patent.
I've been working in a I built my
first AI about 30 years ago and
I've been in the industry for the
last two decades, since before we
called it artificial intelligence,
raul-_1_05-15-2025_110521: Yeah.
dr--rich-kerr_1_05-15-2025_110521:
back when we called it expert systems.
And.
Learning systems and machine learning
and traditional machine learning
now, which is so interesting.
'cause just two years ago it
was called machine learning.
Now it's traditional machine learning.
It's insane.
What's interesting is everybody
always says this time is different.
And
In the, I've ne I haven't seen a wave
of technology in the last two decades
that looks quite like this one.
And specifically with respect to
security and safety, these new
chatbots open up a whole new attack
surface for systems that really.
The data practitioners prior to now
have never really had to think about.
And you have it on both the
defensive side of the ball and
the offensive side of the ball.
So in some instances, if you're just
using the sort of consumer grade
chatbots that are out there, you are
sharing your data with that company.
They're gonna use that
data to train their model.
And you don't know, six months from
now that may show up in an answer
to some other user of the system.
So at an absolute minimum, you
should be using a teams version or
enterprise version of these bots.
The second thing that's
interesting is they're allowing.
The exponential scaling of different
types of, say, phishing attacks and other
things on, on, on that side as well.
It, it's an interesting time to be in
ai but I think it's really critical
to think about the tools that you're
using, making sure that they're vetted,
tested and that you've got a trusted
source to be able to use these tools.
To Cynthia's point around safety and
security over the last two decades, I've
worked with, the 25 man startup all the
way to, I built the data team at PepsiCo.
And so I, I've seen, the problems
that you have as a startup, the
problems you have as a scale up,
the problems you have at massive
enterprise global enterprise scale.
And while some of these questions are
similar, they are absolutely not the same.
On the security side of things, you
want to be able to move very quickly.
As a startup, you want to keep,
maintain that nimbleness, but at
the same time, governance becomes
crucial for you because you don't
want to share your customer's data.
And at the enterprise
side of side of the world.
You have a lot more compliance.
So to Cynthia's point in finance,
in biotech, in biomedical
research the regulatory
elements are pretty significant.
And so again, data governance
becomes a critical element.
And I think we'll even become more
important as we move into the next decade.
raul-_1_05-15-2025_110521: I think it's a
it's almost, I wouldn't say intimidating,
but like when you're starting right
now, to think about these things at
such a high level, it almost forces or
needs the requirement that you have to
talk to an expert in the field or at
least have that consultative outreach.
Like for people listening right now, we're
dr--rich-kerr_1_05-15-2025_110521: Yeah.
raul-_1_05-15-2025_110521: in
creating a new product within their
services or I have one guy who has
his own agency, really successful,
and then from there you build a
separate product outside of that's.
Particularly focused on ai.
Like you have to know
these things because even
dr--rich-kerr_1_05-15-2025_110521: Yeah.
raul-_1_05-15-2025_110521: This
might go a little too deep, but
how MCP can connect everything I
don't trust all those connections.
What's the data layer or
the protection layer there?
Should I actually trust
this connection and
dr--rich-kerr_1_05-15-2025_110521: yeah.
raul-_1_05-15-2025_110521: it's safe?
But a lot to think about as you're
working and building this out.
The interesting point here that to
bring it more practical to a lot
of our listeners is how are you?
AI you can either.
Look down or up, you can look down
like, here's the thing, how we used
to do like compensation or work pay.
Like here's how the traditional way,
and here we're just gonna automate it.
And we're not that you can
automate everything truly right,
dr--rich-kerr_1_05-15-2025_110521: Yeah.
raul-_1_05-15-2025_110521: do what
we did before and use technology
to do that, which I think is great.
Like used cost savings,
efficiency, time saving, et cetera.
But the, there's the flip side of
what's the new potential we can
create that we couldn't do before?
How are you currently looking
at that within the company?
cynthia-abbott-kerr_1_05-15-2025_110521:
Well pay.
I think we can do both.
We can look down and up.
So we can, much to your point, we can,
automate a lot of things that maybe
were pain points for teams prior, that
now with technology we can run smoothly
and not be such a big thing, especially
the competition space in the look up.
It's really a lot of the
predictive modeling that
Has built and saying, we're looking
at economic factors, we're looking at
volatility in the market so that we
can know how impactful pay is gonna be.
Because that's always been the question
mark around okay, we build this now,
but how do we anticipate changes in
three months, six months, nine months?
How do we have a nimble approach?
I.
We live in a very volatile, nimble world.
The market is changing rapidly.
How do we anticipate that?
And
Where the look up for what we're
doing with well pay and the ability
to say, actually this number is
going to either cut down on this
level of retention or increase it.
Here's your volatility number,
company A, depending on
You wanna do.
And we have some businesses
that say, you know what?
We're willing to risk it.
We're willing to pay at this rate,
we're gonna see what happens.
That's perfectly fine.
I found that the predictive
numbers that Richard produces
tend to be highly accurate.
I.
And we've had businesses come back
to us and say, Hey, you were right.
We had X amount of turnover,
or we had x amount of retention
On picking this, this
decision and this outcome.
So I think the look up is the predictive
around how can we anticipate changes in
the market and also helping companies,
predict and anticipate changes around
pay transparency pay equity, it's
no longer just good enough to say.
This is what I pay you.
I now have to explain to you how
that's relevant to the business, to
And I have to track and make sure
that you're not out of alignment with
peers in that level or that role.
Because there could be large
implications if you are out of alignment.
raul-_1_05-15-2025_110521:
then are you putting that data
like it's a turnover increase?
Are you retraining the model for that
specifically so that client has that
experience based on the decision they made
before to do a predictive for the future?
cynthia-abbott-kerr_1_05-15-2025_110521:
Yes, so we build it
specific for each client.
So
Working with you, so the data that we use
for you that will make your model smarter.
We don't then have any
bleed over into business B.
raul-_1_05-15-2025_110521: That's cool.
Yeah, that's important.
cynthia-abbott-kerr_1_05-15-2025_110521:
data feeds you and your experience
and another client's data feeds
them and their experience.
so there's very clear
firewalls between each segment.
But yes, as we train it, it gets smarter
as you come back to it, it remembers.
And as you put more insights into
it, it's gonna say, oh, okay.
This is what you're trying to do, or
here's where you're looking to go.
Got it.
I'm learning from you and your style.
raul-_1_05-15-2025_110521:
No, that's pretty cool.
So it's almost like the longer
use, the better it gets at that
flywheel, that the compounding effect.
To shift gears a little bit, how did you
decide on business model and pricing?
Because just to throw out some
of the options like either
subscription based and sometimes
that's low tier, high tier midtier,
cynthia-abbott-kerr_1_05-15-2025_110521:
Yep.
raul-_1_05-15-2025_110521: value-based
pricing or traditional services and labor.
But you can do more now for the
current retainers or project
scopes than you could in the past.
Like how did you design this, the sweet
spot between that and how what's your
current go-to market pricing strategy?
cynthia-abbott-kerr_1_05-15-2025_110521:
We do a combination of build for
labor and also, retainer and per hour.
Because what we found and Rich and I
talked about this extensively, right?
Like
Founders in the space that have set
rates and then you end up doing more work
than the rate that you've set and you're
taking just a continuous loss, right?
And we've moved into a time now
where people think I'm gonna
pay one price and get 27 things
raul-_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
It's like the Bachanal buffet, right?
You're just out there just
putting everything on your plate.
And so where we landed was retainer
and then billable per hour.
Because even with technology, when you
Working with businesses, every client is
gonna have some level of high touch need.
raul-_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
either through their data debt, either
through their, manager learning whatever
they need and to say universally oh, this
pencil is always gonna be $2 everywhere.
When you get into the human element,
we found we need that flexibility of
saying retainer plus billable one.
We're building a custom solution for you.
And two, it allows us to work and also
stagegate with the client and say,
okay, so we've gone through this much
of retainer and we've done these five
things, and the client says, yes, that
makes sense and I want these other five
things now to run through retainer and
I'm prepared that, billable will kick in.
One fee.
And then, because no matter what,
when you engage with the business,
especially whether you are a compensation
consultant or a business consultant,
when you are a consultant, the
business is gonna hand you everything.
And try to have you solution everything.
And so from that we say, okay, so here's
what it's gonna look like to work with us.
We're very upfront with our pricing
with our clients and say, all
right, here's what this would be.
We sign engagements and we
move forward in the work.
You have more traditional
consultancies that aren't rolling
out artificial intelligence.
To their clients the way we are.
And they're still a, price per hour model.
raul-_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
and then especially in the compensation
space, you're gonna pay different
rates for different levels, right?
So if you're a managing director,
you're gonna make $700 an hour, and if
you're an executive director, you're
gonna get a thousand dollars an hour.
And as
To be responsible for signing
off the invoices, I was like,
how many people joined this call?
What I've got 10 different
hourly rates and price points.
raul-_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
who touched this file?
Like it, it can creep very quickly.
raul-_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
so we have, one billable per hour
rate when you work with well pay.
So you don't have that scope creep
of no, please don't invite the
principal consultant to the call.
We don't need this to balloon because we
really wanna get to the space of helping
our clients make compensation decisions
more efficiently and more quickly.
raul-_1_05-15-2025_110521:
That's all they care about.
Like they, they don't care about the bill.
They do when they're like I don't want
that person here if they're gonna bill
me for X, but they care about the result.
And that was the interesting part that
I want to kind like nuance with you
here because I feel like one, you are,
you're taking something that already
exists, but you're attaching the.
The data and the tech component
too, which is differentiation.
And also the more people that
use it, the better it gets.
You have that network effect.
but the interesting part here is
you're not just selling it like a true
software, which I think is important.
You're still selling it like like
a service enhanced with your.
don't know, your third or fifth, I
don't know how many team members you
have, like with that employee that can
literally do all these things at the
predictive and they don't get tired.
And I think that's an
interesting point here.
'cause I feel like this is gonna
happen a lot in different agencies,
consultancies strategy work.
I.
You name it there we are going to have to
move to a data component in a data layer.
And the pricing will always
be the number one question.
It's do I just add that plus my billable
or it's more outcome-based pricing
at some points or is it a flat fee?
Plus.
So like cost plus.
So it's pretty fascinating
to hear that and see that.
'Cause you're essentially building
out, are you doing like the
entire data lake database and
then analytics of that per client?
dr--rich-kerr_1_05-15-2025_110521:
So interestingly enough you mentioned
that RA gets, RA got, AI gets smarter.
The more clients we do, the AI
actually gets smarter every day.
Anyway.
And part of the reason for that is
we have a, the, and Cynthia mentioned
that I've got patents on a new
class, if you will, of AI systems.
So these are systems
that learn continuously.
They're not the kind of way you
train them one time and then you
use them for inference after that.
These models learn every single day
whether client's using them or not.
And so the.
The difference in the way that we
approach data, the difference in the
way that we approach AI and their
architecture, the difference is pretty
mark is pretty pretty remarkable.
And so the data systems that
we use, again, highly flexible.
So today we're working
on a broad based project.
Tomorrow we want to add inequity.
Day after that, we want
to do executive comp.
The data system will actually
flex to, to the need.
Again, similarly, it's okay, now I have
all the the survey data in the system.
I've got the employee data in the system.
I wanna start tracking.
There, there are some client,
some clients who will help
'em all the way through merit.
So the entire system is designed to be
highly flexible to the client's need.
That's also why it isn't just
a tool that we hand to you.
We're firm believers that AI can do a
lot of things exceedingly well, and there
are some things it does not do well.
And so that's where you need that
human element, that human touch to be
able to de deliver those customized
strategies to those customers.
raul-_1_05-15-2025_110521:
How much is involved?
'cause I thi I see that and
feel that all the time too.
Even though I'm on like
the go to market front.
How much quality assurance are you
doing manually with the work that
you're doing of the stop gaps that
have, I know that you've either
engineered in or prompted in, like how
much actually needs to go through your
filter or a team's a team member's
filter before you ship it to clients?
dr--rich-kerr_1_05-15-2025_110521: Yeah,
so it's probably fair to say that pay
was built as a data and AI system first.
Which we then do compensation on.
So a lot of the quality assurance,
a lot of the model testing, a lot
of the performance testing for
the system is fully automated.
That is to say the AI tests itself or
more precisely one AI tests, another ai.
And we'll identify problem
areas that need my attention.
Some of these systems have been running.
Four and five years without me
having to touch them at all.
And yeah, so again, some of these
the level of proficiency in some of
these systems is exceedingly high.
And in some of them require
a little bit more touch.
Something that the system hasn't seen
as much or hasn't had as much time
interacting with me or with Cynthia.
Definitely needs a little
bit more handholding, but it
also has a way to recognize.
On, its on its own.
The platform itself, Hey, this
is something I know and I can do
well, and this is something I need
a little bit more information.
I I need more clarity from the user.
raul-_1_05-15-2025_110521: Yeah.
And that's one of the key points
that I also wanna highlight here, is
that it's not a magic silver bullet
that'll take care of everything there.
There, you still need to have the human
in the loop, even the orchestrator, to
orchestrate its execution to make sure
that it's actually delivering value.
Have you.
Obviously not in this scenario,
but how have you communicated
the value to clients?
'cause sometimes that's the number
one question that, that everyone,
it in the market tends to ask
is, how do IROI leveraging ai?
And sometimes those use cases, some
people like, it doesn't make sense here.
It does make sense.
But how are you communicating that value?
Or is it through the work
that itself and then the final
outputs, communicates the value?
Or is it the process itself?
Like where do you see the
more the greater gains?
cynthia-abbott-kerr_1_05-15-2025_110521:
I think for our upfront
conversations with clients.
Let's say a prospective clients
reached out to us and says, Hey
we wanna engage in this work.
For us it's the time component.
You could go to a larger
consultancy, you absolutely could.
They're gonna tell you that this work
is gonna take six to nine months.
raul-_1_05-15-2025_110521: Okay.
cynthia-abbott-kerr_1_05-15-2025_110521:
not tell you any timeline at all, and
you'll basically be a vendor manager and
you are gonna be chasing spreadsheets
and junk and clunk and sending it to
them, and then they're gonna lose it.
And then you're gonna have to be a
raul-_1_05-15-2025_110521:
Yeah, it sounds terrible.
That sounds horrible.
That's
cynthia-abbott-kerr_1_05-15-2025_110521:
horrific.
Yes.
I just set at my computer and think,
I went to graduate school for this
dr--rich-kerr_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
and I'm a whole vice president and
an analy a consultant is like, Hey
Cynthia, can you resend me the file?
I sent it to you a month ago.
We have a meeting in a week.
I.
What, what if you've been
doing this whole time,
raul-_1_05-15-2025_110521: It's crazy.
cynthia-abbott-kerr_1_05-15-2025_110521:
What, what is happening?
So I think that for our clients in
the initial, it's a lot of, one, we
can ingest your data in any format.
So I don't have some strange, template
you've gotta fill out to make it work.
Give me everything.
immediately I'm gonna take the weight
and the stress off of you, and I'm
gonna say, just give me everything.
I'm not judging you.
Trust me, we're gonna ingest everything.
Pay Pro is going to highlight and flag
anything we need to review and talk about.
And I'm gonna come back to you I'm gonna
say, okay, so either here's some jobs
that are maybe out of alignment to the
market based on job description, all the
pieces that go into compensation, but you
in the driver's seat to really be the.
Designer and editor.
You don't have to be the spreadsheet
expert, the vendor manager, the
tracker, the tracer, all the things
Can be.
The strategist is really where I think
pay has, such a strong offering to market.
And the fact that because we're using
technology and we can move so quickly,
like what I just outlined here,
would normally take maybe two months.
gonna come back to you
in a matter of days.
And say, so here's what we're seeing.
Here's what we're finding.
What would you like to do?
We can conclude projects in 30 to 45 days.
Because what I always say is,
when you know HR leaders come into
a role, or maybe there's a new
expectation, that the organization
has, you have two types of debt.
You have physical death that you inherit.
And being that you've also both
been people leaders and dealt with
human resource teams, you know how
cumbersome it is to get information.
That's because there's physical
debt and that information is
spread 27 different places,
Right?
15 different ways.
then there's the debt of expectation.
In a business signals, and that
could be your CEO is in favor of
it, your ELT team is in favor of it.
Hey, we need to do some type
of comp analysis, comp work.
Are we aligned to market?
You don't have nine months to come back
to them with a recommendation, with
a solution, with market highlights,
raul-_1_05-15-2025_110521: Because
it changes literally every day.
cynthia-abbott-kerr_1_05-15-2025_110521:
it changes every day.
And they've also moved on.
When you get the buy-in to take
action and have work like this
done, you've gotta move fast.
gotta come back in 30 days and say,
all right, here's what I found.
Here's where I think
we need to make moves.
And the CEO says, okay, you know what?
Yeah.
Or Let's settle on up, but I like this.
I want that.
But when you come back after nine months.
They've
That
raul-_1_05-15-2025_110521:
it's already outdated.
Yeah.
It's.
cynthia-abbott-kerr_1_05-15-2025_110521:
They moved on.
So I think that's where we can really
help the HR function move forward
rapidly, is we can get in and be
the 15 person team in your pocket.
I.
That's going to help you, make
these decisions and shape these
outcomes is where I think we have
the most competitive advantage.
And we, a lot of what Richard's built for
well pay, it also stemmed from the fact
that, in consulting there oftentimes tends
to be this you're a premier consultant.
If you
At a big four.
Or
raul-_1_05-15-2025_110521: Oh yeah.
Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
at, one of these premier survey companies
and I've often held a thesis that with
technology you don't need that, that
raul-_1_05-15-2025_110521: yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
is just as smart as your Aon
consultant that I don't need to have
walked the earth for 60 years and
clank and bang, 15 spreadsheets.
I can have technology that makes me.
Just as smart.
This is really, I think, the next frontier
of being competitive in this space.
And also limiting, the,
all the hands in the pot,
raul-_1_05-15-2025_110521: Yeah,
cynthia-abbott-kerr_1_05-15-2025_110521:
right?
I'm not gonna need 16 people.
I can do it with three.
raul-_1_05-15-2025_110521: That's the
interesting part too, is like the speed
to value, the speed to the outcome.
and then also you, you referenced it
here, but also a project getting done.
months versus like a month also
speaks to like the need or the
potential for value-based pricing,
not just hourly based pricing.
That's one, one of the things that I
found, like I don't have to spend x amount
of hours, 20 hours doing the same thing.
Like I can do more in those 20
hours, but now it's like you can
do it much, much, much faster.
What are some of the and you mentioned
strategy work, and I think this is
where I want to close the loop here.
From my observations, I think
our, like hourly will be obsolete
eventually, depending on if it's
human labor or actually labor.
But the other key thing is I believe that
thinking on thinking which equals strategy
is gonna be one of the most important.
Assets that we can deliver.
'cause we'll either be orchestrators
of different agents or different
workflows that are automated with
leveraging some task-based agents
and reasoning agents big data.
Where do you see this transforming?
'cause I feel like this is a
new era of who know the strategy
and can execute on that.
But now the execution
flow is in another human.
It's either orchestration of multiple
data layers or like multiple AI
agents to, to execute the work.
Where do you stand in terms of the
most important skill sets for today
and also in the next three years?
cynthia-abbott-kerr_1_05-15-2025_110521:
So I'll start and then I think,
rich, you've a lot of insight in here
because we're seeing it in, Moderna
just combined their HR and IT teams.
So we're seeing these skill sets overlap.
We're seeing these skill sets,
it's actually, it blooms taxonomy.
What can you do with the
information that you have?
Can you think strategically?
Can you make recommendations?
And also, the workforce going forward,
you're gonna have people that are
responsible for managing these agents.
And, rich has also built agents
for other businesses, manage
them, put safety guards in place.
Because I think to, to your point,
ra, we're gonna see, I think less.
Hourly worker.
But we're also gonna
see more gig work as a
Of technology and agents.
Gen Z does not wanna take any
type of leadership role or path.
There's a new study that just came out
that said millennials are exhausted.
We millennial here, we feel like
we've been just smooshed between, the
decision makers and the workforce.
And it, it
Led to the outcomes we
thought it would lead to.
And that Gen Z is listen, just
pay me for the projects I work on.
I wanna live out of my trailer
and drive around the country.
I'm just not trying to be embedded
in all of these businesses.
So I think
We're gonna see that shift
because ultimately you need.
You need people that can run
technology to, achieve certain
outcomes for a business.
raul-_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
I think we're gonna move away from the
traditional you work here, you have
all these, years that you work here,
Model.
Just because the work, the expectation
of the workforce, the technology.
It is changing as well.
And that you still have
though demand for output.
So these businesses I think are gonna
have to move how they think about
labor and technology to be successful.
But Rich, curious to get your thoughts.
'cause I know you,
dr--rich-kerr_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
a lot of these trends and
dr--rich-kerr_1_05-15-2025_110521: Yeah.
cynthia-abbott-kerr_1_05-15-2025_110521:
About it in, in large detail.
dr--rich-kerr_1_05-15-2025_110521:
So first of all, I thoroughly agree
with what Cynthia's talking about and
I think technical skills are still
critically important in the AI space.
But what is really interesting about
how these systems are evolving and what
makes this wave of AI very different
than anything we've seen in the last
couple of decades is the number of
times I've put my product hat on
and the number of times I've put my.
Leadership hat on.
A lot of times if you're trying to
get the best out of these models, you
have to be pretty descriptive in terms
of what you're asking them to do.
And in a way that's a type of leadership.
'cause if you're asking Pete, whether
it's, whether you're asking AI agents
or folks to follow you and to do a thing
that you need done you've gotta give
them an idea of what it is you need done.
So being clear about how you scope
a question or an issue for these AI
agents, I think is critically important.
And so are there technical elements Sure.
Will those become less important as data
solutions and AI orchestration to your
point earlier becomes more ubiquitous?
Absolutely.
But I think the kind of back to
the core skill around how do you.
How do you give clear direction and use
systems in a way that helps them get
to the answer you need to get them to,
becomes more critical going forward.
So leadership to me is a massive unlock.
And I think that's true whether
you're working with AI systems or
continuing to work with other humans.
There, there's a, in my mind,
it's one of the largest gaps
really in, in the economy.
Trillions of dollars lost to inefficiency.
Really down to bad
leadership, bad management.
raul-_1_05-15-2025_110521: Yeah.
dr--rich-kerr_1_05-15-2025_110521:
of engagement of employees, across
the US really speaks to that.
The disengagement, broad disengagement
of of Gen Z says the same thing.
And nobody wants to be a people
manager 'cause they've seen
those middle managers, those.
Those early career managers get
absolutely hammered between the
employees that are complaining and the
senior management, ridiculous demands.
I think it's something of a lost art and
a space that it was never easy if you
will, I've been training managers for
two decades and it's never been an easy
thing to help people, lead other people.
And.
raul-_1_05-15-2025_110521:
themselves first.
dr--rich-kerr_1_05-15-2025_110521:
For sure, a hundred percent.
You gotta start with being able to manage
self before you can manage anything else.
But I do think that it's
actually gotten worse over time.
I think that the level of demand
and the complexity has actually
gotten higher while at the same
time the level of training and and
interactivity has actually dropped off.
So I actually think it's harder today
than it was 10 years ago, 20 years ago.
raul-_1_05-15-2025_110521: Yeah, a mix of
culture, a mix of technology, also, what's
happening on the macro macroeconomics.
It's pretty fascinating to see.
so then what's the solve like?
What do you think is if we go back to the
dr--rich-kerr_1_05-15-2025_110521: yeah.
raul-_1_05-15-2025_110521: key skillset.
dr--rich-kerr_1_05-15-2025_110521:
Being a leader is.
Part of it is embedded
in your personality.
I think there, there's a core curiosity.
You know what led me to leadership was
just down to really that curiosity of
trying to understand how things work and
then realizing that the bigger the problem
I needed to solve or wanted to solve,
the more scale I needed, the more other
very smart people I needed to work with.
And that led me to that space
of saying, okay, how do I.
Gather together a group of incredibly
smart people, smartest people in
the world to solve a very complex
and difficult problem that very few
people are right now care about.
But five years from now is
gonna be critically important.
It started with working on
antibiotics in our food supply.
It is me and a research group that got
together that said, listen, I think we
can take antibiotics out of poultry,
cynthia-abbott-kerr_1_05-15-2025_110521:
Okay.
dr--rich-kerr_1_05-15-2025_110521:
And make our food supply safer.
And we said, okay.
We figured that out.
Then we did the same
thing for dairy products.
Then we started looking
at things in shellfish.
So almost all the things that you eat
every day in some way, shape or form,
are affected by the work of me and my
colleagues who started out with how do
we solve this massive problem to improve
public health or to make food more
accessible in a way that people aren't
really thinking about right now, but
five years from now, 10 years from now.
Critically important.
Yeah.
raul-_1_05-15-2025_110521:
It's fascinating curiosity on
frameworks, communicating that
with others, and also being
dr--rich-kerr_1_05-15-2025_110521: Yeah,
raul-_1_05-15-2025_110521: with self.
I think it boils down to of the
spark, but also communication.
Even when you're chatting with the LLM.
dr--rich-kerr_1_05-15-2025_110521:
that's a hundred percent right.
A hundred percent.
So that's where I think it starts.
And to the extent that we
as leaders today, can help.
Tomorrow's leaders get into those
to spark that curiosity, to get
them interested in solving bigger
and larger, world style problems.
I I think that's absolutely
something we should be doing.
And frankly, need to be giving back more.
raul-_1_05-15-2025_110521: I like that
better be on your mission statement
also because it's a bigger mission
of how you're tackling that problem.
But,
dr--rich-kerr_1_05-15-2025_110521: Yeah.
raul-_1_05-15-2025_110521: Cynthia
Rich, I appreciate you both being
on, but for our listeners, where's
the best place for them to follow
your work and see what you're up to?
cynthia-abbott-kerr_1_05-15-2025_110521:
Certainly we're very active on LinkedIn.
So I'm Cynthia Abbott Kerr on LinkedIn.
and you can always go out to our website.
Pay ai.
There's a calendar link on the website
if you'd like to connect with us.
We're always happy to talk all
things compensation and ai and
thank you so much for having us on.
It's been a pleasure.
raul-_1_05-15-2025_110521: It is been fun.
Put all those links in the show
notes and we'll go from here.
dr--rich-kerr_1_05-15-2025_110521:
Thank you so much.
cynthia-abbott-kerr_1_05-15-2025_110521:
Thank you.
Thank you for listening to the podcast.
If you'd like to get more of
these podcasts, please go ahead
and subscribe to wherever you're
watching or listening to the pod.
If you have any suggestions or questions
that you want me to answer on the
pod, or you have a guest that you want
me to interview, please go ahead and
email me all of your suggestions and
questions at podcast at do good work.
io that's podcast at do good work.
io.
If you'd like to give me public
feedback, you can go on Apple
Podcasts, and from there, you
can leave up to a 5 star review.
I would greatly appreciate that.
If you'd like more free resources where
you can get my best strategies to help you
increase your company's performance and
scale profitably, where you can get hand
picked articles to propel your growth, and
you can get trainings and discussions that
I give freely online, as well as low cost
resources, Such as my books and guides.
You can get all of that
by going to dogoodwork.
io forward slash resources 90 percent
of all these resources are not behind
any email opt ins you can get instant
access by going to dogoodwork.
io forward slash resources Now, if
you'd like to accelerate your progress
and shorten the gap between information
and action and start seeing results
in your business, let's work together
to increase your company's performance
and scale profitably and serve
more clients without the overwhelm.
You can request a free clarity call
to see how we can best support you to
reach your goals by going to DoGoodWork.
io forward slash apply.
Again, that's DoGoodWork.
io forward slash apply.
As always, it's an honor to be
a small part in your journey.
This is Raul Hernandez.
Do good work.